Update README.md

README.md

@@ -6,11 +6,12 @@ base_model:
 pipeline_tag: text-to-video
 ---
 # rCM: Score-Regularized Continuous-Time Consistency Model
+# Causal-rCM: Teacher-Forcing meets Self-Forcing in Autoregressive Diffusion Distillation for Streaming Video Generation and Interactive World Models
 [**Paper**](https://arxiv.org/abs/2510.08431) | [**Website**](https://research.nvidia.com/labs/dir/rcm) | [**Code**](https://github.com/NVlabs/rcm)
 
-This repo holds converted Wan official checkpoints in rCM/TurboDiffusion style. 
+This repo holds converted Wan official checkpoints in (Causal-)rCM/TurboDiffusion style. 
 
-Specifically, rCM equivalently replaces the Conv3d layer in the original Wan with a Linear layer for patch embedding, facilitating further optimization. The layer weight is directly reshaped without value change, e.g., from shape [5120, 16, 1, 2, 2] (Conv3d) to shape [5120, 64] (Linear).
+Specifically, (Causal-)rCM equivalently replaces the `Conv3d` layer in the original Wan with a `Linear` layer for patch embedding, facilitating further optimization. The layer weight is directly reshaped without value change, e.g., from shape [5120, 16, 1, 2, 2] (Conv3d) to shape [5120, 64] (Linear).
 
 ## Citation
 
@@ -21,4 +22,10 @@ Specifically, rCM equivalently replaces the Conv3d layer in the original Wan wit
   journal={arXiv preprint arXiv:2510.08431},
   year={2025}
 }
+@article{zheng2026causal,
+  title={Causal-rCM: Teacher-Forcing meets Self-Forcing in Autoregressive Diffusion Distillation for Streaming Video Generation and Interactive World Models},
+  author={Zheng, Kaiwen and He, Guande and Zhao, Min and Zhu, Hongzhou and Zhang, Jintao and Chen, Huayu and Chen, Jianfei and Lin, Chen-Hsuan and Liu, Ming-Yu and Zhu, Jun and Ma, Qianli},
+  journal={TODO},
+  year={2026}
+}
 ```